One of the problems occurring in spectrometry is noise that arises from electronic sensor fluctuations, illumination fluctuations, as well as time-varying transmission due to process flow variations, density gradients, dust, and the like. Conventional tunable diode laser absorption spectroscopy (TDLAS) systems and many other spectroscopic measurement systems often experience degradation in performance due to various noise sources.
A typical prior art spectrometry measurement is described, for example, in U.S. Pat. No. 8,711,357 to Liu et al, which provides for a reference and test harmonic absorption curves from a laser absorption spectrometer having a tunable or scannable laser light source and a detector. The absorption curves are generated by the detector in response to light passing from the laser light source through respective reference and sample gas mixtures. The reference curve might be determined for the spectrometer in a known or calibrated state. The shape of the test harmonic absorption curve is compared with that of the reference harmonic absorption curve and parameters of the laser absorption spectrometer are adjusted to reduce the difference and correct the test curve shape.
U.S. Pat. No. 6,940,599 to Hovde describes, spectral demodulation in absorption spectrometry, wherein the spectral response of a detector can be characterized in Fourier space.
However, neither of these methods deals directly with the presence of noise in the absorption signal. They would each perform better if the noise could first be reduced or removed from the signal obtained from the detector.
Typically, conventional spectroscopic signal analysis will pre-process the signal using simple averaging of successive measurements or traces obtained \ from multiple scans of the laser wavelengths. It does not use any weighted average or determine any optimal weighting scheme based on realistic noise models. As such, while this simple averaging may be adequate in r laboratory or ideally-controlled conditions, in more harsh or uncontrolled measurement environments it may suffer unacceptable degradation of performance due to an inability to reduce the noise in the signal sufficiently. Beyond a certain limit, the systems can no longer operate and report data reliably due to insufficient noise suppression. This is a recurring problem for any field-deployed TDLAS systems or any spectroscopic system used in an environment where harsh real-world conditions such as dust, density gradients, temperature gradients, and mechanical movement can lead to noise.
It is desired, to provide processing schemes that can suppress noise so as to improve overall sensor performance and extend the range of conditions under—which spectroscopic systems can reliably operate. Noise levels from a variety of sources due to electronics, laser fluctuation, or time-varying transmission through the process flow should be able to be successfully reduced.